crate version maybe out of date compared to example

[Raj2032]

I am coding from scratch instead of cloning the entire repo, so this is my code so far:

use std::{collections::VecDeque, path::PathBuf};

use image;
use ocrs::{OcrEngine, OcrEngineParams};
use rten;

const SAMPLE_CONTENTS_DIR: &str = "testing_images";
const MODELS_DIR: &str = "models";

mod ocrs_extras;
/// Read a file from a path that is relative to the crate root.
//fn read_file(path: &str) -> Result<Vec<u8>, std::io::Error>
fn read_file(path: &str) -> Vec<u8>
{
    //let mut abs_path = PathBuf::from(env!("CARGO_MANIFEST_DIR"));
    let mut abs_path = PathBuf::new();
    abs_path.push(path);
    return std::fs::read(abs_path).unwrap();
}
struct Args
{
    image: String,
}
//fn parse_args() -> Result<Args, lexopt::Error>
fn parse_args() -> Result<Args, lexopt::Error>
{
    use lexopt::prelude::*;

    let mut values = VecDeque::new();
    let mut parser = lexopt::Parser::from_env();

    while let Some(arg) = parser.next()?
    {
        match arg
        {
            Value(val) => values.push_back(val.string()?),
            Long("help") =>
            {
                println!(
                    "Usage: {bin_name} <image>",
                    bin_name = parser.bin_name().unwrap_or("hello_ocrs")
                );
                std::process::exit(0);
            }
            _ => return Err(arg.unexpected()),
        }
    }

    let image = values.pop_front().ok_or("missing `image` arg")?;

    Ok(Args{image})
}
fn main()
{
    //let args = parse_args().unwrap();
    //let img = Image::from_path(&format!("{}/large_sign.jpg", SAMPLE_CONTENTS_DIR)).unwrap();
    //let img = Image::from_path(&format!("{}/mobile_speed.jpeg", SAMPLE_CONTENTS_DIR)).unwrap();
    //let img = Image::from_path(&format!("{}/small_sign.jpeg", SAMPLE_CONTENTS_DIR)).unwrap();

    let detection_model_data = read_file(&format!("{}/text-detection.rten", MODELS_DIR));
    let rec_model_data = read_file(&format!("{}/text-recognition.rten", MODELS_DIR));

    let detection_model = rten::Model::load(&detection_model_data).unwrap();
    let recognition_model = rten::Model::load(&rec_model_data).unwrap();

    let engine = OcrEngine::new(OcrEngineParams
    {
        detection_model: Some(detection_model),
        recognition_model: Some(recognition_model),
        ..Default::default()
    }).unwrap();

    let img = image::open(&format!("{}/image.jpeg", SAMPLE_CONTENTS_DIR)).map(|image| image.into_rgb8()).unwrap();

    //ocrs_extras::preprocess::test();
    let img_source = ocrs_extras::preprocess::ImageSource::from_bytes(img.as_raw(), img.dimensions()).unwrap();
    let ocr_input = engine.prepare_input(img_source).unwrap(); // Error

}

However on this line:

let ocr_input = engine.prepare_input(img_source).unwrap(); // Error I have an error:

error[E0308]: mismatched types
  --> src/main.rs:77:42
   |
77 |     let ocr_input = engine.prepare_input(img_source).unwrap();
   |                            ------------- ^^^^^^^^^^ expected `TensorBase<f32, &[f32], NdLayout<3>>`, found `ImageSource<'_>`
   |                            |
   |                            arguments to this method are incorrect
   |
   = note: expected struct `TensorBase<f32, &[f32], NdLayout<3>>`
              found struct `ImageSource<'_>`

I pretty much copied most of the code.

Inside lib.rs (from your own repo)

ocrs/ocrs/src/lib.rs

Line 87 in ea67c9e

pub fn prepare_input(&self, image: ImageSource) -> anyhow::Result<OcrInput> {

This is the code:

    /// Preprocess an image for use with other methods of the engine.
    pub fn prepare_input(&self, image: ImageSource) -> anyhow::Result<OcrInput> {
        Ok(OcrInput {
            image: prepare_image(image),
        })
    }

which is only taking ImageSource as the argument, which differs from the error that I am getting.

please note inside ocrs_extras::preprocess is a file that I created and contains the exact copy of preprocess.rs from https://github.com/robertknight/ocrs/blob/main/ocrs/src/preprocess.rs

[robertknight]

There have indeed been some API changes on the main branch, which is what the example builds against. If you navigate to the most recent tag in this repository, you can find a version of the example that builds with the most recently published crate version: https://github.com/robertknight/ocrs/blob/ocrs-v0.6.0/ocrs/examples/hello_ocr.rs.

[Raj2032]

Are the new changes going to be pushed to the crate library soon or I have to link the crate to the repo (e.g. ocrs = "<link_to_repo>")?

If I have to link to the repo then what is the exact link I should use?

[robertknight]

I would suggest to use the code from the older version of the example I linked above to get started. That will work with the published version of the ocrs crate. I will publish a new version of the crate soon, hopefully some time in the next week.

[Raj2032]

@robertknight Ok cool thanks mate :)